Module 1
Relational Data and Query Foundations
- Tables, rows, columns, keys and relationships
- SELECT, aliases and calculated fields
- WHERE, ORDER BY and logical conditions
- Nulls, data types and query discipline
Foundation and Data
SQL and Data Modelling for Business Analytics
Query, combine and model relational data to create reusable analytical datasets for reporting, dashboards and decision support.
Course overview
Build the data-access capability behind reliable business analytics.
SQL and Data Modelling for Business Analytics develops practical querying and modelling skills for professionals who need to work directly with relational data.
Participants progress from query logic and filtering through aggregation, joins, subqueries, common table expressions and analytical functions, then connect those skills with dimensional modelling and reusable dataset design.
The course emphasises correctness, traceability and analytical usefulness rather than database administration.
Learning outcomes
What participants will be able to do.
- Explain relational database structures and keys.
- Write SELECT queries using filtering, sorting and calculated fields.
- Aggregate data using grouping and appropriate functions.
- Combine data using joins, subqueries and common table expressions.
- Use window functions for analytical comparisons and rankings.
- Identify data-grain and duplicate risks in query results.
- Design basic dimensional models using facts and dimensions.
- Create a documented analytical dataset for reporting or modelling.
Who should attend
Designed for professionals who use data, analysis or evidence to improve decisions.
- Business and data analysts.
- BI and reporting professionals.
- Business analysts who need direct data access.
- Finance, operations and performance analysts.
- Professionals preparing for more advanced analytics work.
Prerequisites
Professionally relevant and application-focused.
Basic data literacy is expected. Previous SQL experience is not required, although participants should be comfortable working with tables, fields and business measures.
Course structure
A five-Module journey from analytical understanding to workplace application.
The sequence may be delivered across five days or adapted to another approved format while preserving the learning outcomes and the five connected Modules.
Module 2
Aggregation and Business Measures
- GROUP BY and aggregate functions
- Distinct values and counting correctly
- Date, text and numeric transformations
- Business measures and denominator control
Module 3
Joining and Structuring Data
- Inner and outer joins
- Join keys, cardinality and duplicate risk
- Subqueries and common table expressions
- Building multi-step analytical queries
Module 4
Analytical SQL and Data Modelling
- Window functions, rankings and running totals
- Operational versus analytical models
- Fact tables, dimensions and grain
- Star schemas and conformed dimensions
Module 5
Reusable Analytical Datasets and Quality
- Query validation and reconciliation
- Documentation and lineage
- Performance awareness and maintainability
- Integrated SQL case and analytical dataset build
Learning experience
Move from understanding to application, production and workplace value.
Understand
Connect concepts with business decisions
Clarify methods, assumptions, evidence requirements and the decision context before applying tools.
Apply
Work through realistic analytical cases
Use datasets, scenarios and decision questions to practise analytical judgement in context.
Produce
Create practical analytical outputs
Develop artefacts that can be adapted to reporting, modelling, governance or decision-support work.
Review
Challenge evidence and analytical choices
Use peer review, validation criteria and facilitated critique to improve analytical reasoning.
Transfer
Apply the learning at work
Identify how to adapt the methods to organisational data, decisions, systems and governance requirements.
Completion requirements
Demonstrate participation, application and professional judgement.
- Participate actively in case discussions, data exercises and analytical workshops.
- Complete the principal analytical or decision-support outputs assigned during the programme.
- Contribute to the integrated case, model, dashboard or application workshop.
- Complete knowledge checks and a workplace application or study plan.
Participant outputs
Leave with practical analytical artefacts.
- SQL query workbook or script set.
- Join and data-grain validation checklist.
- Analytical measures catalogue.
- Dimensional model sketch.
- Reusable analytical dataset specification.
- Query QA and documentation checklist.
Delivery options
Select the learning format that fits your people and analytical environment.
Instructor-led
Live Classroom
Facilitated face-to-face learning with analytical cases, datasets, modelling tasks, discussion and immediate feedback.
Instructor-led
Live Virtual Classroom
Interactive online delivery using collaborative workspaces, data exercises, breakout analysis and guided model development.
Flexible
Blended Learning
A structured combination of preparation, live facilitation, applied assignments, analytical work and follow-up application.
Organisation-specific
Corporate and In-Company
Tailored delivery aligned with organisational datasets, measures, tools, governance, decisions and analytics maturity where appropriate.
Frequently asked questions
Course information and participation.
Which SQL platform is used?
The course teaches portable SQL concepts. Exercises can be adapted to an approved database or training environment, recognising that syntax varies by platform.
Do I need programming experience?
No. The course starts with relational and query fundamentals and builds progressively.
Does the course cover database administration?
No. The focus is analytical querying and data modelling rather than infrastructure, security administration or database operations.
Can the course use our data model?
Yes. Corporate delivery can incorporate approved schemas, reporting structures and business measures.
Does completion provide professional certification?
The course develops practical SQL and analytical data-modelling capability and may provide an INDENTRA course-completion record where applicable. It is not a third-party certification.
Take the next step
Build direct, reliable access to the data behind business decisions.
Discuss a hands-on SQL programme aligned with your organisation’s data platform, reporting model and analytical use cases.